GaN HEMT Electrothermal Modeling Using Feedback Neural Networks Technique

被引：1

作者：

Jarndal, Anwar ^{[1
]}

机构：

[1] Univ Sharjah, Elect Engn Dept, Sharjah, U Arab Emirates

来源：

2019 INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTING TECHNOLOGIES AND APPLICATIONS (ICECTA) | 2019年

关键词：

GaN MEMT; Large-signal modeling; Neural Networks;

D O I：

10.1109/icecta48151.2019.8959622

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Thermal effect represents a main challenge for GaN high electron mobility transistor (HEMT) especially for Si-substrate based device under high power of operation. This paper addresses this issue by developing an efficient and simple feedback neural network (FNN) based electrothermal model. The model has been applied on a packaged GaN HEMT and implemented on advanced design software (ADS). The model showed a very good agreement with large-signal measurements at different classes of operation.

引用

页数：4

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